SNP (Single Nucleotide Polymorphism) molecular marker for detecting dairy cow somatic cell score correlation and application thereof

Abstract

The invention specifically discloses three SNP (Single Nucleotide Polymorphism) molecular markers obviously related to Chinese Holstein cattle somatic cell scoring (SCS) and application thereof. The SNP is located in the following aspects: 1) in a No.8 chromosome 15818198bp (LINGO2 gene, Ggt; t), genotype effect GGlt; gTlt; GTlt; tT; 2), in the 17th chromosome 16535314bp (Ggt in the ZNF330 gene; a), effect GGlt; aA1t; AA1t; gA; 3) in the 69672126bp (in the PACS2 gene, Ggt; a), effect GGlt; gAlt; aA. SCS is an index of mastitis, and high SCS corresponds to high morbidity rate of mastitis. By detecting the genotypes of the sites, individuals with low SCS (namely, low mastitis morbidity) can be accurately bred in the early stage, the disease-resistant breeding efficiency and accuracy are remarkably improved, the reduction of the mastitis morbidity of groups is accelerated, and the production performance and economic benefits are improved.

Description

Technical Field

[0001] The invention belongs to the technical field of molecular biology and relates to SNP molecular markers for detecting somatic cell scores of dairy cows and applications thereof. Background Art

[0002] Bovine mastitis is widely recognized as one of the most devastating and prevalent diseases in the global dairy industry. The prevalence of clinical and latent mastitis in dairy farms ranges from 46.6% to 85.7%, meaning the vast majority of dairy herds are afflicted. This disease not only leads to a sharp decline in milk production and severe deterioration in milk quality (e.g., reduced milk protein content, increased somatic cell counts, and the potential for pathogenic bacteria or antibiotic residues) in affected cows, significantly reducing the economic value and food safety of raw milk, but also results in high veterinary costs, significant losses from premature culling of cows due to illness, and arduous care for sick cows. It is estimated that mastitis causes tens of billions of dollars in economic losses to the global dairy industry annually, representing a major bottleneck to improving the quality, efficiency, and sustainable development of the dairy industry. For a long time, strategies for mastitis prevention and control have focused primarily on environmental hygiene management, optimizing milking processes, vaccination, and treatment with antibiotics. While these measures have been effective in controlling clinical incidence and reducing losses, they often address only the symptoms and not the root cause, and face challenges such as increasing drug resistance and drug residue regulations. Crucially, existing research has been relatively limited and in-depth in exploring the intrinsic genetic factors influencing the development and progression of mastitis in dairy cows, namely the key genes and their molecular mechanisms of action. This lack of understanding of the genetic basis has severely hampered efforts to fundamentally improve mastitis resistance in dairy cows through genetic breeding. Therefore, further exploration of key genes with mastitis resistance effects and identification of molecular markers useful for breeding are not only of great theoretical significance for scientifically elucidating the genetic mechanisms of mastitis development, but also lay an indispensable foundation for establishing an efficient and precise dairy cow disease-resistant breeding technology system to fundamentally reduce the incidence of disease in the herd.

[0003] Genetic improvement of mastitis resistance in dairy cows faces a core biological challenge: clinical mastitis itself, as a typical binary trait (onset / absence), has a generally low heritability (h²) estimate, typically ranging from 0.02 to 0.06. This low heritability means that phenotypic variation in this trait is primarily influenced by environmental factors (such as husbandry, sanitation, and pathogen exposure) and non-additive genetic effects, while additive genetic effects (i.e., those that can be exploited by selection) account for a very small proportion. This results in extremely low efficiency of phenotypic selection based directly on clinical mastitis incidence records in traditional breeding practices, slowing genetic progress and failing to meet the urgent need for rapid improvement of herd resistance in practical production. To overcome this bottleneck, scientists have turned their attention to intermediate traits closely related to mastitis—somatic cell count (SCC) and its conversion metric, somatic cell score (SCS). Somatic cells in milk are primarily composed of white blood cells (macrophages, lymphocytes, and neutrophils), and they are a key indicator of the immune response of the dairy cow's mammary gland to infection (primarily bacterial invasion). When the mammary gland is infected or irritated, the somatic cell count increases significantly. The SCS is a normally distributed score derived from the actual SCC through mathematical transformation, which is more consistent with statistical analysis requirements. First, the heritability estimates of SCS are significantly higher than those of clinical mastitis, generally ranging from 0.10 to 0.20, making it a medium-heritability trait, indicating a higher degree of genetic control and making it more suitable as a breeding target. Second, SCS can be conveniently, economically, and widely obtained through conventional dairy performance index (DHI), resulting in a large and highly standardized data set, making it well-suited for breeding applications. Numerous genetic studies have confirmed a highly significant positive genetic correlation between SCS and mastitis incidence (particularly mastitis), with correlation coefficients ranging from 0.30 to 0.98. This suggests that individuals with low SCS are generally more resistant to mastitis at the genetic level. Therefore, major international and domestic dairy cattle breeding organizations have incorporated SCS as a core breeding target trait into their comprehensive selection indices (such as TPI and CPI). Through continuous selection and genetic improvement of SCS, they indirectly and effectively reduce the incidence of mastitis in herds. Using SCS as an indicator trait for mastitis resistance in breeding has become a standard strategy for disease-resistant dairy cattle.

[0004] However, while phenotypic selection based on SCS is more effective than direct selection for clinical mastitis, it still has certain limitations: SCS is typically measured after milk production, requiring a long selection cycle; the phenotypic value itself is still affected by the environment; and the accuracy of assessing genetic potential needs to be improved. To more accurately select high-quality cattle with low SCS (i.e., high mastitis resistance) earlier (e.g., during the calving stage), marker-assisted selection (MAS) technology has shown great potential. The key lies in identifying molecular markers, such as single nucleotide polymorphisms (SNPs), that are stably and significantly associated with SCS (and, therefore, mastitis resistance) and whose effects can be explained. Genome-wide association studies (GWAS) have become one of the most powerful tools in recent years for mapping quantitative trait loci (QTLs) that influence complex quantitative traits such as SCS. By simultaneously examining the associations of hundreds of thousands or even millions of SNPs across the genome with a target trait (SCS), it can efficiently identify genomic regions with significant associations without prior hypotheses. Existing studies have often employed GWAS, combining the known biological functions of genes within these significantly associated regions (such as those involved in immune response, inflammation regulation, apoptosis, and barrier function) to identify and validate candidate genes and key SNPs that influence SCS or mastitis resistance. This approach significantly narrows the target regions, improving the specificity of functional gene discovery and providing important guidance for dairy cattle genetics and breeding. Despite this, for Chinese Holstein cattle, a dominant breed in China, the number of reported key SCS molecular markers with clear effects and robust suitability for large-scale breeding remains relatively limited. There is an urgent need to utilize modern genomic technologies, such as GWAS, to identify more novel, highly effective SNP markers in the Chinese Holstein population and clarify their modes of action. This will further improve and optimize molecular breeding techniques for mastitis resistance and enhance the accuracy and efficiency of selection.

[0005] Based on the significant need for mastitis prevention and control in dairy cows, the core position of SCS as a key proxy trait, the technological trend of molecular marker-assisted selection, and the shortcomings of existing GWAS studies in discovering efficient MAS markers suitable for Chinese Holstein cattle, the core objectives of this study focus on: using genomic strategies such as genome-wide association analysis (GWAS) to conduct systematic research in the Chinese Holstein cattle population, aiming to identify new single nucleotide polymorphism (SNP) molecular marker sites that have a highly significant association with somatic cell score (SCS), a key indicator of mastitis resistance, and have stable effects. By deeply analyzing the genotype effect patterns of these sites, a direct and reliable genetic basis will be provided for the establishment of a molecular marker-assisted breeding platform for mastitis resistance in Chinese Holstein cattle, ultimately serving to improve the health level and economic benefits of the population. Summary of the Invention

[0006] The present invention aims to address the above-mentioned issues by providing a SNP molecular marker for detecting somatic cell score-related SNPs in dairy cows and its application. Based on whole-genome sequencing data and GWAS analysis from 380 Chinese Holstein cattle, the present invention identifies candidate variant sites associated with somatic cell score in dairy cows. This allows for better understanding of the pathogenesis and molecular mechanisms of mastitis in dairy cows and the selection of cows for resistance to mastitis, thereby fundamentally improving the physical fitness and health of dairy cows and reducing breeding costs.

[0007] In order to achieve the above object, the technical solution adopted by the present invention is:

[0008] The SNP molecular markers associated with the somatic cell score of dairy cows include at least one of the following markers:

[0009] Marker 1: Located at 15818198bp on chromosome 8 of the dairy cow genome ARS-UCD version 2.0. The base of this site is G or T, corresponding to the 51st nucleic acid site in the nucleic acid sequence table SEQ ID NO.1;

[0010] Marker 2: Located at 16535314bp on chromosome 17 of the dairy cow genome ARS-UCD version 2.0. The base of this site is G or A, corresponding to the 51st nucleic acid site in the nucleic acid sequence table SEQ ID NO.2;

[0011] Marker 3: Located at 69672126bp on chromosome 21 of the ARS-UCD2.0 version of the dairy cow genome. The base of this site is G or A, corresponding to the 51st nucleic acid site in the nucleic acid sequence table SEQ ID NO.3.

[0012] The present invention also provides a use of the SNP molecular marker in the selection or auxiliary selection of dairy cow breeds or lines and dairy cow somatic cell scores, specifically in the selection or auxiliary selection of dairy cows with high / low dairy cow somatic cell scores.

[0013] The present invention also provides a method for selecting or assisting in the selection of buffalo breeds or lines related to dairy cow somatic cell scores using the SNP molecular markers, the specific steps of which are:

[0014] Extracting cow genomic DNA, detecting nucleotide 15818198 of chromosome 8 of the cow genome, detecting that the sequence of nucleotide 15818198 is G or T, determining whether the genotype of the tested cow is GG, GT, or TT, and selecting cows with the GG gene for further selection and / or breeding as needed; the somatic cell score of the GG gene cow is lower than that of the GT or TT gene cows;

[0015] Extracting dairy cow genomic DNA, detecting nucleotide 16535314 of chromosome 17 of the dairy cow genome, detecting that the sequence of nucleotide 16535314 is G or A, determining whether the genotype of the tested dairy cow is GG, GA, or AA, and selecting dairy cows with the GG gene for further selection and / or breeding as needed; the somatic cell score of the dairy cows with the GG gene is lower than that of the dairy cows with the GT or TT gene;

[0016] The cow's genomic DNA is extracted and the nucleotide at position 69672126 of chromosome 21 of the cow's genome is detected. The sequence of the nucleotide at position 9672126 is detected to be G or A, and the genotype of the tested cow is determined to be GG, GA or AA. Cows with the GG gene are selected for the next step of seed selection and / or breeding as needed; the somatic cell score of the GG gene cow is lower than that of the GT or TT type cows.

[0017] In the present invention, it is further stated that the genotype of chromosome 8 of the dairy cow is GG or TT, which respectively indicates that the nucleotide at position 15818198 is a homozygote of G or a homozygote of T;

[0018] The genotype of the dairy cow's chromosome 17 is GG or AA, which respectively indicates that the nucleotide at position 16535314 is a homozygous G or a homozygous A;

[0019] The genotype of the No. 21 chromosome of the dairy cow is GG or AA, which respectively indicates that the nucleotide at position 69,672,126 is a homozygous G or a homozygous A.

[0020] The application further provides a SNP typing detection kit, comprising specific primer pairs and / or probes for amplifying or detecting the three SNP sites described above, wherein the amplification region covers the 51st SNP site in the sequence shown in SEQ ID NO: 1-3.

[0021] The application further provides application of the SNP molecular marker described above to breeding or assisting breeding of a high-mastitis-resistant dairy cow breed or strain.

[0022] Due to the technical scheme described above, the application has the following beneficial effects:

[0023] The present invention identified for the first time three SNP sites that are highly significantly associated with somatic cell score (SCS) in the Chinese Holstein cattle genome (reference genome version: ARS-UCD1.2), and clarified their precise genomic location, allele variation type, and genotype effect. Among them, at 15818198bp on chromosome 8 (located in the LINGO2 gene), the base at this site is G in the reference genome, and a base substitution of G>T occurs. Association analysis showed that there are significant differences in SCS between individuals with different genotypes, and the effect is manifested in the somatic cell score of GG genotype dairy cows. <GT基因型奶牛的体细胞评分<TT基因型奶牛的体细胞评分;第17号染色体第16535314bp处(位于ZNF330基因中),该位点处参考基因组的碱基是G,发生G> The base substitution of A, association analysis showed that there were significant differences in SCS between individuals with different genotypes, and its effect was manifested in the somatic cell score of GG genotype cows. <AA基因型奶牛的体细胞评分<GA基因型奶牛的体细胞评分;和第21号染色体第69672126bp处(位于PACS2基因中),该位点处参考基因组的碱基是G,发生G> The base substitution of A, association analysis showed that there were significant differences in SCS between individuals with different genotypes, and its effect was manifested in the somatic cell score of GG genotype cows. <GA基因型奶牛的体细胞评分<AA基因型奶牛的体细胞评分。研究发现该3个SNP分子标记与中国荷斯坦牛体细胞评分显著相关,可用于中国荷斯坦牛体细胞评分的分子标记辅助育种,加快选育良种中国荷斯坦牛。体细胞评分越高,则对应的体细胞数越高,奶牛患乳房炎的概率越大;体细胞评分越低,则对应的体细胞数越低,奶牛患乳房炎的概率越低。由此可知在实际育种中通过对上述3个SNP位点进行检测,可以通过选育选育体细胞评分高 / 低的奶牛从而指导留种乳腺炎抗病高 / 低的奶牛,有助于奶牛乳腺炎抗病育种的效率和准确性,从而有效降低群体乳腺炎的整体发病率。这将直接减少因乳腺炎导致的产奶量损失、弃奶、治疗费用和奶牛过早淘汰,显著改善牛群健康水平,延长奶牛生产寿命,最终大幅提升奶牛养殖的生产性能和经济效益。 BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 This is a Manhattan plot of the genome-wide association analysis of somatic cell scoring in Chinese Holstein cattle. Explanation of the accompanying figures: The markers above the dotted line represent the 10 somatic cell scoring SNP molecular markers screened by the present invention, which are distributed on chromosomes 4, 6, 8, 9, 15, 17, 21, and 29 of dairy cows, respectively.

[0025] Figure 2This is a QQ graph of somatic cell scores from the genome-wide association analysis of Chinese Holstein cattle of the present invention.

[0026] Figure 3 This is a box plot of the somatic cell score distribution of individuals with different genotypes at the SNP8_15818198 site of Chinese Holstein cattle in the present invention.

[0027] Figure 4 This is a box plot of the somatic cell score distribution of individuals with different genotypes at the SNP17_16535314 site in Chinese Holstein cattle in the present invention.

[0028] Figure 5 This is a box plot of the somatic cell score distribution of individuals with different genotypes at the SNP21_69672126 site of Chinese Holstein cattle in the present invention.

[0029] “*” indicates that the P value between the two genotypes is significantly different; “****” indicates that the P value between the two genotypes is extremely significantly different. DETAILED DESCRIPTION

[0030] The specific implementation of the invention is further described below with reference to the accompanying drawings.

[0031] Example 1 Screening of SNP sites related to somatic cell scoring in dairy cows

[0032] 1. Sample collection and DNA preparation: 380 Chinese Holstein cows were selected, and DNA from each individual was prepared using the Tiangen blood genomic DNA extraction kit.

[0033] 2. Phenotype collection and breeding value estimation: 1,038 lactation records and somatic cell scores were collected from 380 Holstein cows, covering 2015 to 2023. Single-trait animal models were used to estimate breeding values ​​(EBVs) for each trait, and denormalized EBVs (dEBVs) were calculated for each trait in combination with pedigree information.

[0034] The model is as follows: y = Xb + Z1α + Z2p + e,

[0035] Where y is the phenotypic value, X is the fixed effect matrix, b is the fixed effect variable such as farm year (HYS), calving year (CY), calving season (CS) or parity; Z1 is the animal individual additive effect matrix; Z2 is the animal permanent environment effect matrix; e is the residual effect; α is the animal individual additive effect, and p is the permanent environment effect.

[0036] The collected phenotypic data were statistically analyzed using R language. The somatic cell score traits of 380 Chinese Holstein cattle from 2015 to 2023 were analyzed, and the results are shown in Table 1.

[0037] Table 1 Statistical analysis of somatic cell scores in Chinese Holstein cattle

[0038]

[0039] From the above table, we can see that the average value of the SCS trait is 2.92, its heritability is 0.14, which is medium heritability, and its reliability is 0.26.

[0040] 3. SNP typing: Whole-genome resequencing was used to characterize 380 individuals. SNP typing was performed using GATK 4.2 software, followed by genotype imputation using Beagle 5.4 software. Population SNP filtering was performed using PLINK software. Filtering criteria were as follows: individual call rate exceeding 97%; SNP detection rate exceeding 95%; minimum allele frequency (MAF) greater than 0.05; and Hardy-Wingerbo equilibrium test P value less than 10. -6 Finally, 380 individuals and 1,030,098 SNPs were used for subsequent analysis.

[0041] 4. Genome-wide Association Analysis: GWAS analyses of somatic cell score traits were performed using the FarmCPU method within rMVP software. The kinship matrix and four principal components were used as covariates. GWAS p-values ​​were corrected using Boferroni. The GWAS signal selection threshold was 0.05 / N, where N was 1,030,098.

[0042] The results are as follows Figures 1-2 As shown in the figure, a Manhattan plot shows genetic marker effect values ​​(i.e., genome-wide P values ​​obtained through the F test) ranked by physical location on the chromosome. The horizontal axis represents physical location on the chromosome, and the vertical axis represents -log10P. Smaller P values ​​indicate stronger associations, as indicated by larger vertical axes. The horizontal dashed line in the Manhattan plot represents the significance level. When -log10(P) > 5, the SNP is considered significantly associated with the trait. A qq plot (Quantile-quantile plot) shows the distribution of actual P values ​​versus the expected P value under the null hypothesis of no association. It is used to examine the effects of population stratification and individual relatedness on association analyses. If the observed P value differs from the expected P value only at the rightmost end of the distribution, it indicates that the trait is not caused by population stratification. QQ plots are primarily used to estimate the discrepancy between observed and predicted values ​​for quantitative traits. Quantitative trait data are generally normally distributed. In GWAS studies, the X and Y axes of a QQ plot primarily represent the -logP values ​​of each SNP. The predicted line is a dashed line extending at a 45° angle from the origin.

[0043] Depend on Figure 1 It can be seen that 10 significant GWAS signals associated with somatic cell score traits were identified, which were distributed on chromosomes 4, 6, 8, 9, 15, 17, 21 and 29 of dairy cows. Figure 2 The QQ plot further confirms the reliability of the analysis results. Table 2 further provides detailed information on these significant SNPs. It can be seen that three SNPs are located within genes, indicating that these SNPs are more relevant to gene function and will serve as the focus of subsequent analysis.

[0044] Table 2 Information of the 10 molecular markers screened

[0045]

[0046]

[0047] Next, we used one-way ANOVA to detect the differences in somatic cell scores among the three genotypes of Chinese Holstein cattle, used T-test to compare the somatic cell scores between different genotypes, and used box plots to visually display the distribution of somatic cell scores of individuals with different genotypes ( Figure 3 、 4 , 5);

[0048] The higher the somatic cell score, the higher the corresponding somatic cell count, and the greater the probability of the cow suffering from mastitis; the lower the somatic cell score, the lower the corresponding somatic cell count, and the lower the probability of the cow suffering from mastitis; it can be used as a molecular marker to identify the mastitis resistance of Chinese Holstein cattle to assist breeding and be applied in production.

[0049] like Figure 3 As shown, the box plot shows the distribution of the three genotypes (GG, GT, TT) of the SNP site 8_15818198_G_T in the somatic cell score of Chinese Holstein cattle; it can be seen that the somatic cell score breeding value of dairy cows carrying the GG genotype is the lowest, and the corresponding somatic cell count is the least, indicating that the GG genotype can be used as a marker for the selection of mastitis resistance in dairy cows.

[0050] As shown in Table 3, the three genotypes of SNP locus 8_15818198_G_T significantly affected the somatic cell score of Chinese Holstein cattle (one-way ANOVA P.value (P value) < 0.05 was considered significant; two-way T-test P.value (P value) < 0.05 was considered significant). Among them, the somatic cell score of GG Chinese Holstein cattle was significantly lower than that of TT Chinese Holstein cattle (P < 0.05).

[0051] Table 3 Correlation analysis between molecular marker SNP 8_15818198_G_T and somatic cell score of Chinese Holstein cattle

[0052]

[0053] like Figure 4As shown, the box plot shows the distribution of the three genotypes (GG, GA, AA) of the SNP site 17_16535314_G_A in the somatic cell score of Chinese Holstein cattle; it can be seen that the somatic cell score breeding value of dairy cows carrying the GG genotype is the lowest, and the corresponding somatic cell count is the least, indicating that the GG genotype can be used as a marker for the selection of mastitis resistance in dairy cows.

[0054] As shown in Table 4, the three genotypes of SNP site 17_16535314_G_A all significantly affected the somatic cell score of Chinese Holstein cattle (one-way ANOVA P.value (P value) < 0.05 was considered to be significantly different; two-way T-test P.value (P value) < 0.05 was considered to be significantly different). Among them, the somatic cell score of GG type Chinese Holstein cattle was significantly lower than that of GA type Chinese Holstein cattle (P < 0.05).

[0055] Table 4 Correlation analysis between molecular marker SNP 17_16535314_G_A and somatic cell score of Chinese Holstein cattle

[0056]

[0057] like Figure 5 As shown, the box plot shows the distribution of the three genotypes (GG, GA, AA) of the SNP site 21_69672126_G_A in the somatic cell score of Chinese Holstein cattle; it can be seen that the somatic cell score breeding value of dairy cows carrying the GG genotype is the lowest, and the corresponding somatic cell count is the least, indicating that the GG genotype can be used as a marker for the selection of mastitis resistance in dairy cows.

[0058] As shown in Table 5, the three genotypes of the SNP site 21_69672126_G_A significantly affected the somatic cell score of Chinese Holstein cattle (one-way ANOVA P.value (P value) < 0.05 was considered significant; two-way T-test P.value (P value) < 0.05 was considered significant). Among them, the somatic cell score of GG Chinese Holstein cattle was significantly lower than that of AA Chinese Holstein cattle (P < 0.05).

[0059] Table 5 Correlation analysis between molecular marker SNP21_69672126_G_A and somatic cell score of Chinese Holstein cattle

[0060]

[0061] Example 2

[0062] Study the application of the above three SNP marker primer sets in the detection of somatic cell score in Chinese Holstein cattle

[0063] The method for SNP molecular marker breeding / assisted breeding of Chinese Holstein cattle breeds or lines related to Chinese Holstein cattle somatic cell score of the present application can be applied, and the method is:

[0064] Extract genomic DNA from Chinese Holstein cattle, detect the deoxynucleotide at position 15818198 of chromosome 8, detect the deoxynucleotide at position 15818198 as G or T, and determine whether the genotype of the Chinese Holstein cattle to be tested is GG, GT or TT. According to breeding requirements, Chinese Holstein cattle with GG, GT or TT genes are selected and / or bred in the next step. The somatic cell score of the GG gene cow is much lower than that of GT or TT. And / or

[0065] Extracting genomic DNA from Chinese Holstein cattle, detecting the deoxynucleotide at position 16535314 of chromosome 17, detecting the deoxynucleotide at position 16535314 as G or A, determining whether the genotype of the Chinese Holstein cattle to be tested is GG, GA or AA, and selecting Chinese Holstein cattle with GG, GA or AA gene types for the next step of breeding and / or breeding according to breeding requirements. The somatic cell score of the GG gene cow is lower than that of the GA or AA type. And / or

[0066] Genomic DNA of Chinese Holstein cattle is extracted, and deoxynucleotides at position 69672126 of chromosome 21 are detected. The deoxynucleotides at position 69672126 are detected to be G or A, and the genotype of the tested Chinese Holstein cattle is determined to be GG, GA or AA. According to breeding requirements, Chinese Holstein cattle with GG, GA or AA gene types are selected for the next step of breeding and / or breeding. The somatic cell score of the GG gene cows is lower than that of the GA or AA types.

[0067] Example 3

[0068] A SNP typing detection kit comprises specific primer pairs and / or probes for amplifying or detecting the three SNP sites described in Example 1, wherein the amplified region covers the 51st SNP site in the sequences shown in SEQ ID NOs: 1-3. A person skilled in the art can easily design primers for amplifying the molecular markers or probes for identifying the molecular markers based on the molecular genetic markers of the present invention, thereby detecting the molecular genetic markers, for example, by amplifying the molecular genetic markers by PCR and then cloning and sequencing to obtain the corresponding sequences, or by detecting the Bsm-RFLP polymorphism.

[0069] Example 4

[0070] The present invention also provides a use of the above-mentioned SNP molecular marker in breeding or assisting in breeding a dairy cow breed or line with high resistance to mastitis, wherein the method is:

[0071] Extract genomic DNA from Chinese Holstein cattle, detect the deoxynucleotide at position 15818198 of chromosome 8, detect the deoxynucleotide at position 15818198 as G or T, and determine whether the genotype of the Chinese Holstein cattle to be tested is GG, GT or TT. According to breeding requirements, select Chinese Holstein cattle with high mastitis resistance GG gene for the next step of selection and / or breeding. And / or

[0072] Extract genomic DNA from Chinese Holstein cattle, detect the deoxynucleotide at position 16535314 of chromosome 17, detect the deoxynucleotide at position 16535314 as G or A, and determine whether the genotype of the Chinese Holstein cattle to be tested is GG, GA or AA. According to breeding requirements, select Chinese Holstein cattle with high mastitis resistance GG gene for the next step of selection and / or breeding. And / or

[0073] Genomic DNA of Chinese Holstein cattle is extracted, and the deoxynucleotide at position 69672126 of chromosome 21 is detected. The deoxynucleotide at position 69672126 is detected to be G or A, and the genotype of the tested Chinese Holstein cattle is determined to be GG, GA or AA. According to breeding requirements, Chinese Holstein cattle with a high mastitis resistance GG type gene are selected for the next step of selection and / or breeding.

[0074] The above description is a detailed description of the preferred embodiments of the present invention, but the embodiments are not intended to limit the scope of the patent application of the present invention. Any equivalent changes or modifications completed under the technical spirit suggested by the present invention should fall within the patent scope covered by the present invention.

Claims

1. A SNP molecular marker associated with somatic cell scoring in dairy cows, characterized by: The SNP molecular markers related to the cow somatic cell score include at least one of the following markers: Marker 1: Located at 15818198bp on chromosome 8 of the dairy cow genome ARS-UCD version 2.

0. The base of this site is G or T, corresponding to the 51st nucleic acid site in the nucleic acid sequence table SEQ ID NO.1; Marker 2: Located at 16535314bp on chromosome 17 of the dairy cow genome ARS-UCD version 2.

0. The base of this site is G or A, corresponding to the 51st nucleic acid site in the nucleic acid sequence table SEQ ID NO.2; Marker 3: Located at 69672126bp on chromosome 21 of the ARS-UCD2.0 version of the dairy cow genome. The base of this site is G or A, corresponding to the 51st nucleic acid site in the nucleic acid sequence table SEQ ID NO.

3.

2. A use of the SNP molecular marker according to claim 1 in the selection or auxiliary selection of dairy cattle breeds or lines and somatic cell scoring of dairy cattle, specifically in the selection or auxiliary selection of dairy cattle with high / low somatic cell scores.

3. A method for selecting or assisting in the selection of buffalo breeds or lines related to dairy cow somatic cell scores using the SNP molecular markers of claim 1, characterized in that: The specific steps are: Extracting cow genomic DNA, detecting nucleotide 15818198 of chromosome 8 of the cow genome, detecting that the sequence of nucleotide 15818198 is G or T, determining whether the genotype of the tested cow is GG, GT, or TT, and selecting cows with the GG gene for further selection and / or breeding as needed; the somatic cell score of the GG gene cow is lower than that of the GT or TT gene cows; Extracting dairy cow genomic DNA, detecting nucleotide 16535314 of chromosome 17 of the dairy cow genome, detecting that the sequence of nucleotide 16535314 is G or A, determining whether the genotype of the tested dairy cow is GG, GA, or AA, and selecting dairy cows with the GG gene for further selection and / or breeding as needed; the somatic cell score of the dairy cows with the GG gene is lower than that of the dairy cows with the GT or TT gene; The cow's genomic DNA is extracted and the nucleotide at position 69672126 of chromosome 21 of the cow's genome is detected. The sequence of the nucleotide at position 9672126 is detected to be G or A, and the genotype of the tested cow is determined to be GG, GA or AA. Cows with the GG gene are selected for the next step of seed selection and / or breeding as needed; the somatic cell score of the GG gene cow is lower than that of the GT or TT type cows.

4. The method according to claim 3, characterized in that The genotype of chromosome 8 of the dairy cow is GG or TT, which respectively indicates that the nucleotide at position 15818198 is a homozygote of G or a homozygote of T; The genotype of the dairy cow's chromosome 17 is GG or AA, which respectively indicates that the nucleotide at position 16535314 is a homozygous G or a homozygous A; The genotype of the No. 21 chromosome of the dairy cow is GG or AA, which respectively indicates that the nucleotide at position 69,672,126 is a homozygous G or a homozygous A.

5. A SNP typing detection kit, characterized in that: It comprises a specific primer pair and / or probe for amplifying or detecting the three SNP sites according to claim 1, and the amplified region covers the 51st SNP site in the sequence shown in SEQ ID NO: 1-3.

6. Use of the SNP molecular marker according to claim 1 in breeding or assisting in breeding dairy cow breeds or lines with high resistance to mastitis.

Images